AIMC Topic: Cross-Sectional Studies

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Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent t...

Patients' Attitudes Toward the Use of Artificial Intelligence as a Diagnostic Tool in Radiology in Saudi Arabia: Cross-Sectional Study.

JMIR human factors
BACKGROUND: Artificial intelligence (AI) is widely used in various medical fields, including diagnostic radiology as a tool for greater efficiency, precision, and accuracy. The integration of AI as a radiological diagnostic tool has the potential to ...

Identifying Factors Associated With Fast Visual Field Progression in Patients With Ocular Hypertension Based on Unsupervised Machine Learning.

Journal of glaucoma
PRCIS: We developed unsupervised machine learning models to identify different subtypes of patients with ocular hypertension in terms of visual field (VF) progression and discovered 4 subtypes with different trends of VF worsening. We then identified...

Nursing Students' Personality Traits and Their Attitude toward Artificial Intelligence: A Multicenter Cross-Sectional Study.

Journal of nursing management
BACKGROUND: Despite the importance of studying factors contributing to nursing students' attitudes toward artificial intelligence, yet according to our knowledge, no study has addressed the relationship between personality traits and the attitude of ...

ChatGPT and retinal disease: a cross-sectional study on AI comprehension of clinical guidelines.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To evaluate the performance of an artificial intelligence (AI) large language model, ChatGPT (version 4.0), for common retinal diseases, in accordance with the American Academy of Ophthalmology (AAO) Preferred Practice Pattern (PPP) guidel...

Artificial Intelligence for Early Detection of Pediatric Eye Diseases Using Mobile Photos.

JAMA network open
IMPORTANCE: Identifying pediatric eye diseases at an early stage is a worldwide issue. Traditional screening procedures depend on hospitals and ophthalmologists, which are expensive and time-consuming. Using artificial intelligence (AI) to assess chi...

Effects of environmental phenols on eGFR: machine learning modeling methods applied to cross-sectional studies.

Frontiers in public health
PURPOSE: Limited investigation is available on the correlation between environmental phenols' exposure and estimated glomerular filtration rate (eGFR). Our target is established a robust and explainable machine learning (ML) model that associates env...

Can digital leadership transform AI anxiety and attitude in nurses?

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
BACKGROUND: The lack of artificial intelligence applications in nursing education and the nursing profession in Turkey and the need for strategies for integrating artificial intelligence into the nursing profession continues. At this point, there is ...

A machine learning approach to determine the risk factors for fall in multiple sclerosis.

BMC medical informatics and decision making
BACKGROUND: Falls in multiple sclerosis can result in numerous problems, including injuries and functional loss. Therefore, determining the factors contributing to falls in people with Multiple Sclerosis (PwMS) is crucial. This study aims to investig...